def testPeirceTest5(self):
values = [61.1080599488, 34.876110084, 63.0380528016, -37.3907919689, 55.7742201359, 158.950985878, 152.580838711, 159.962185469,
39.5242231825, 167.478815798, -45.1721895276, 150.966989049, 38.7181950131, 54.4126758063, 62.9191496902, -41.4928983793,
46.5057394648, -36.3803547969, -48.513237809, 61.4695459467]
result = peirceTest.peirceTest( values )
self.failUnless(result)
v,obj = result
# print 'number of outliers at size: '+repr(n)+ ' =',len(obj)
self.assertTrue(len(v) == 10)
self.assertTrue(len(obj) == 10)
def testPeirceTest4(self):
values = []
n = 2 # Default value 200. Tested up to 10,000 once before.
for i in range(n):
values.append(i)
result = peirceTest.peirceTest(values)
self.failUnless(result)
v, obj = result
# print 'number of outliers at size: '+repr(n)+ ' =',len(obj)
self.assertTrue(len(v) == n)
self.assertTrue(len(obj) == 0)
def testPeirceTest4(self):
values = []
n = 2 # Default value 200. Tested up to 10,000 once before.
for i in range(n):
values.append(i)
result = peirceTest.peirceTest( values )
self.failUnless(result)
v,obj = result
# print 'number of outliers at size: '+repr(n)+ ' =',len(obj)
self.assertTrue(len(v) == n)
self.assertTrue(len(obj) == 0)
def testPeirceTest1(self):
values = [101.2, 90.0, 99.0, 102.0, 103.0, 100.2, 89.0, 98.1, 101.5, 102.0]
vOld,_oOld = peirceTest.peirceTestOld( values )
# print 'v=',vOld
# print vOld.av, vOld.sd
# print 'o=',_oOld
#
v,_o = peirceTest.peirceTest( values )
# print 'v=',v
# print v.av, v.sd
# print 'o=',_o
self.assertTrue( vOld == v )
def testPeirceTest1(self):
values = [
101.2, 90.0, 99.0, 102.0, 103.0, 100.2, 89.0, 98.1, 101.5, 102.0
]
vOld, _oOld = peirceTest.peirceTestOld(values)
# print 'v=',vOld
# print vOld.av, vOld.sd
# print 'o=',_oOld
#
v, _o = peirceTest.peirceTest(values)
# print 'v=',v
# print v.av, v.sd
# print 'o=',_o
self.assertTrue(vOld == v)
def testPeirceTest5(self):
values = [
61.1080599488, 34.876110084, 63.0380528016, -37.3907919689,
55.7742201359, 158.950985878, 152.580838711, 159.962185469,
39.5242231825, 167.478815798, -45.1721895276, 150.966989049,
38.7181950131, 54.4126758063, 62.9191496902, -41.4928983793,
46.5057394648, -36.3803547969, -48.513237809, 61.4695459467
]
result = peirceTest.peirceTest(values)
self.failUnless(result)
v, obj = result
# print 'number of outliers at size: '+repr(n)+ ' =',len(obj)
self.assertTrue(len(v) == 10)
self.assertTrue(len(obj) == 10)
def testPeirceTest3(self):
#Note the difference between array sizes 17 and 18.
#No outliers identified at 18 but 7 outliers made the cutoff at size 17
values = []
n = 200 # Default value 200. Tested up to 10,000 once before.
m = 10 # Only tested with default value 10.
for i in range(0,n):
values.append(1)
# nTdebug("n=", len(values))
for i in range(0,m):
values[i] = 2
while n > 3:
values = values[:n]
_v,obj = peirceTest.peirceTest( values )
# print 'number of outliers at size: '+repr(n)+ ' =',len(obj)
self.assertTrue(len(obj)<=m)
n -= 1
def testPeirceTest3(self):
#Note the difference between array sizes 17 and 18.
#No outliers identified at 18 but 7 outliers made the cutoff at size 17
values = []
n = 200 # Default value 200. Tested up to 10,000 once before.
m = 10 # Only tested with default value 10.
for i in range(0, n):
values.append(1)
# nTdebug("n=", len(values))
for i in range(0, m):
values[i] = 2
while n > 3:
values = values[:n]
_v, obj = peirceTest.peirceTest(values)
# print 'number of outliers at size: '+repr(n)+ ' =',len(obj)
self.assertTrue(len(obj) <= m)
n -= 1
def testPeirceTest2(self):
# A stable array just longer than the reference data used in the test.
values = []
for i in range(0, 1000):
values.append(1)
# nTdebug("n=",len(values))
for i in range(0, 10):
values[i] = 2
# Will only note first 9 outliers
vOld, oOld = peirceTest.peirceTestOld(values)
# print 'v=',vOld
# print vOld.av, vOld.sd
# print 'obj=',oOld
#
v, obj = peirceTest.peirceTest(values)
# print 'v=',v
# print v.av, v.sd
# print 'obj=',obj
self.assertFalse(vOld == v)
self.assertFalse(oOld == obj)
def testPeirceTest2(self):
# A stable array just longer than the reference data used in the test.
values = []
for i in range(0,1000):
values.append(1)
# nTdebug("n=",len(values))
for i in range(0,10):
values[i] = 2
# Will only note first 9 outliers
vOld,oOld = peirceTest.peirceTestOld( values )
# print 'v=',vOld
# print vOld.av, vOld.sd
# print 'obj=',oOld
#
v,obj = peirceTest.peirceTest( values )
# print 'v=',v
# print v.av, v.sd
# print 'obj=',obj
self.assertFalse( vOld == v )
self.assertFalse( oOld == obj )
def plotTestHistoDihedral():
nTdebug("Starting plotTestHistoDihedral")
ps = NTplotSet() # closes any previous plots
ps.hardcopySize = (600, 369)
graphicsFormat = "png"
residueName = "ASN1"
dihedralName = "CHI1"
dihedralNameLatex = "$\chi 1$"
project = Project('plotTestHistoDihedral')
plotparams = project.plotParameters.getdefault(dihedralName,
'dihedralDefault')
binsize = int(plotparams.ticksize /
12) # 60 over 12 results in 5 degrees. as an int
bins = (plotparams.max - plotparams.min) / binsize # int
angleList = NTlist(50, 60, 51, 53, 52, 54, 62, 90, 93)
angleList.cAverage()
goodAndOutliers = peirceTest(angleList)
if not goodAndOutliers:
nTerror("No goodAndOutliers in plotTestHistoDihedral")
return True
angleList.good, angleList.outliers = goodAndOutliers
angleList.limit(plotparams.min,
plotparams.max) # Actually not plotted angle anymore.?
angleList.cAverage(plotparams.min, plotparams.max)
angleList.good.limit(plotparams.min, plotparams.max, byItem=1)
angleList.good.cAverage(plotparams.min, plotparams.max, byItem=1)
angleList.outliers.limit(plotparams.min, plotparams.max, byItem=1)
angleList.outliers.cAverage(plotparams.min, plotparams.max, byItem=1)
for i, angleL in enumerate([angleList, angleList.good,
angleList.outliers]):
nTdebug("angleL %d: %s" % (i, str(angleL)))
nTdebug(" cav: %s" % angleL.cav)
# end for
xTicks = range(int(plotparams.min), int(plotparams.max + 1),
plotparams.ticksize)
# nTdebug("xTicks: " + repr(xTicks))
# figWidth = 600
# figHeight = None # Golden which turns out to be 369
# figHeight = figWidth * golden_mean
plot = NTplot(title=residueName,
xRange=(plotparams.min, plotparams.max),
xTicks=xTicks,
xLabel=dihedralNameLatex,
yLabel='Occurrence')
ps.addPlot(plot)
if not angleList.__dict__.has_key('good'):
nTerror("angleList.__dict__.has_key('good')")
return True
plot.histogram(angleList.good.zap(1),
plotparams.min,
plotparams.max,
bins,
attributes=boxAttributes(fillColor=plotparams.color))
if angleList.__dict__.has_key('outliers'):
plot.histogram(angleList.outliers.zap(1),
plotparams.min,
plotparams.max,
bins,
attributes=boxAttributes(fillColor=plotparams.outlier),
valueIndexPairList=angleList.outliers)
# aAv = angleList.cav
aAv = angleList.good.cav
width = 4.0
lower, upper = 45, 55
alpha = 0.3
ylim = plot.get_ylim()
ylimMax = 5 # Just assume.
if ylim is not None:
ylimMax = ylim[1]
# note plotparams.lower is a color!
bounds = NTlist(lower, upper)
bounds.limit(plotparams.min, plotparams.max)
if bounds[0] < bounds[1]: # single box
point = (bounds[0], 0) # lower left corner of only box.
sizes = (bounds[1] - bounds[0], ylimMax)
# nTdebug("point: " + repr(point))
# nTdebug("sizes: " + repr(sizes))
plot.box(point, sizes,
boxAttributes(fillColor=plotparams.lower, alpha=alpha))
else: # two boxes
# right box
point = (bounds[0], 0) # lower left corner of first box.
sizes = (plotparams.max - bounds[0], ylimMax)
# nTdebug("point: " + repr(point))
# nTdebug("sizes: " + repr(sizes))
plot.box(point, sizes,
boxAttributes(fillColor=plotparams.lower, alpha=alpha))
point = (plotparams.min, 0) # lower left corner of second box.
sizes = (bounds[1] - plotparams.min, ylimMax)
# nTdebug("point: " + repr(point))
# nTdebug("sizes: " + repr(sizes))
plot.box(point, sizes,
boxAttributes(fillColor=plotparams.lower, alpha=alpha))
# plot.line( (lower, 0), (lower, ylimMax),
# lineAttributes(color=plotparams.lower, width=width) )
# plot.line( (upper, 0), (upper, ylimMax),
# lineAttributes(color=plotparams.upper, width=width) )
#
# Always plot the cav line
# pylint: disable=E1102
plot.line((aAv, 0), (aAv, ylimMax),
lineAttributes(color=plotparams.average, width=width))
# dashdotline() )
fnBase = "testPlotHistoDihedral"
if True:
fn = fnBase + '.png'
else:
i = 0
fn = None
while not fn or os.path.exists(fn):
i += 1
fn = fnBase + '_' + str(i) + '.png'
ps.hardcopy(fn, graphicsFormat)
def plotTestHistoDihedral():
nTdebug("Starting plotTestHistoDihedral")
ps = NTplotSet() # closes any previous plots
ps.hardcopySize = (600,369)
graphicsFormat = "png"
residueName = "ASN1"
dihedralName= "CHI1"
dihedralNameLatex= "$\chi 1$"
project = Project('plotTestHistoDihedral')
plotparams = project.plotParameters.getdefault(dihedralName,'dihedralDefault')
binsize = int(plotparams.ticksize / 12 ) # 60 over 12 results in 5 degrees. as an int
bins = (plotparams.max - plotparams.min)/binsize # int
angleList = NTlist( 50,60, 51, 53, 52, 54, 62, 90, 93 )
angleList.cAverage()
goodAndOutliers = peirceTest( angleList )
if not goodAndOutliers:
nTerror("No goodAndOutliers in plotTestHistoDihedral")
return True
angleList.good, angleList.outliers = goodAndOutliers
angleList.limit( plotparams.min, plotparams.max ) # Actually not plotted angle anymore.?
angleList.cAverage( plotparams.min, plotparams.max )
angleList.good.limit( plotparams.min, plotparams.max, byItem=1 )
angleList.good.cAverage( plotparams.min, plotparams.max, byItem=1 )
angleList.outliers.limit( plotparams.min, plotparams.max, byItem=1 )
angleList.outliers.cAverage( plotparams.min, plotparams.max, byItem=1 )
for i,angleL in enumerate( [angleList, angleList.good, angleList.outliers] ):
nTdebug("angleL %d: %s" % (i, str(angleL)))
nTdebug(" cav: %s" % angleL.cav)
# end for
xTicks = range(int(plotparams.min), int(plotparams.max+1), plotparams.ticksize)
# nTdebug("xTicks: " + repr(xTicks))
# figWidth = 600
# figHeight = None # Golden which turns out to be 369
# figHeight = figWidth * golden_mean
plot = NTplot(title = residueName,
xRange = (plotparams.min, plotparams.max),
xTicks = xTicks,
xLabel = dihedralNameLatex,
yLabel = 'Occurrence'
)
ps.addPlot(plot)
if not angleList.__dict__.has_key('good'):
nTerror("angleList.__dict__.has_key('good')")
return True
plot.histogram( angleList.good.zap(1),
plotparams.min, plotparams.max, bins,
attributes = boxAttributes( fillColor=plotparams.color )
)
if angleList.__dict__.has_key('outliers'):
plot.histogram( angleList.outliers.zap(1),
plotparams.min, plotparams.max, bins,
attributes = boxAttributes( fillColor=plotparams.outlier),
valueIndexPairList=angleList.outliers
)
# aAv = angleList.cav
aAv = angleList.good.cav
width = 4.0
lower, upper = 45, 55
alpha = 0.3
ylim = plot.get_ylim()
ylimMax = 5 # Just assume.
if ylim is not None:
ylimMax = ylim[1]
# note plotparams.lower is a color!
bounds = NTlist(lower, upper)
bounds.limit(plotparams.min, plotparams.max)
if bounds[0] < bounds[1]: # single box
point = (bounds[0], 0) # lower left corner of only box.
sizes = (bounds[1]-bounds[0],ylimMax)
# nTdebug("point: " + repr(point))
# nTdebug("sizes: " + repr(sizes))
plot.box(point, sizes, boxAttributes(fillColor=plotparams.lower, alpha=alpha))
else: # two boxes
# right box
point = (bounds[0], 0) # lower left corner of first box.
sizes = (plotparams.max-bounds[0],ylimMax)
# nTdebug("point: " + repr(point))
# nTdebug("sizes: " + repr(sizes))
plot.box(point, sizes, boxAttributes(fillColor=plotparams.lower, alpha=alpha))
point = (plotparams.min, 0) # lower left corner of second box.
sizes = (bounds[1]-plotparams.min,ylimMax)
# nTdebug("point: " + repr(point))
# nTdebug("sizes: " + repr(sizes))
plot.box(point, sizes, boxAttributes(fillColor=plotparams.lower, alpha=alpha))
# plot.line( (lower, 0), (lower, ylimMax),
# lineAttributes(color=plotparams.lower, width=width) )
# plot.line( (upper, 0), (upper, ylimMax),
# lineAttributes(color=plotparams.upper, width=width) )
#
# Always plot the cav line
# pylint: disable=E1102
plot.line( (aAv, 0), (aAv, ylimMax), lineAttributes(color=plotparams.average, width=width) )
# dashdotline() )
fnBase = "testPlotHistoDihedral"
if True:
fn = fnBase + '.png'
else:
i=0
fn = None
while not fn or os.path.exists(fn):
i += 1
fn = fnBase + '_' + str(i) + '.png'
ps.hardcopy(fn, graphicsFormat)
